6 citations · 7 across the 6 of their papers we have counts for
7 papers
Generative deep learning for foundational video translation in ultrasound
Nikolina Tomic, Roshni Bhatnagar, Sarthak Jain +4
Deep learning (DL) has the potential to revolutionize image acquisition and interpretation across medicine, however, attention to data imbalance and missingness is required. Ultras…
SecureBERT 2.0: Advanced Language Model for Cybersecurity Intelligence
Ehsan Aghaei, Sarthak Jain, Prashanth Arun +1
Effective analysis of cybersecurity and threat intelligence data demands language models that can interpret specialized terminology, complex document structures, and the interdepen…
Self-supervised Analogical Learning using Language Models
Ben Zhou, Sarthak Jain, Yi Zhang +4
Large language models have been shown to suffer from reasoning inconsistency issues. That is, they fail more in situations unfamiliar to the training data, even though exact or ver…
ViBe: A Text-to-Video Benchmark for Evaluating Hallucination in Large Multimodal Models
Vipula Rawte, Sarthak Jain, Aarush Sinha +9
Recent advances in Large Multimodal Models (LMMs) have expanded their capabilities to video understanding, with Text-to-Video (T2V) models excelling in generating videos from textu…
LLM Agents Improve Semantic Code Search
Sarthak Jain, Aditya Dora, Ka Seng Sam +1
Code Search is a key task that many programmers often have to perform while developing solutions to problems. Current methodologies suffer from an inability to perform accurately o…
MMLU-SR: A Benchmark for Stress-Testing Reasoning Capability of Large Language Models
Wentian Wang, Sarthak Jain, Paul Kantor +3
We propose MMLU-SR, a novel dataset designed to measure the true comprehension abilities of Large Language Models (LLMs) by challenging their performance in question-answering task…
From Instructions to Constraints: Language Model Alignment with Automatic Constraint Verification
Fei Wang, Chao Shang, Sarthak Jain +6
User alignment is crucial for adapting general-purpose language models (LMs) to downstream tasks, but human annotations are often not available for all types of instructions, espec…